Advanced Intelligent Systems | |
Textile‐Based Inductive Soft Strain Sensors for Fast Frequency Movement and Their Application in Wearable Devices Measuring Multiaxial Hip Joint Angles during Running | |
Christopher Napier1  JingYang Peng1  Tyler J. Cuthbert1  Mohammad Tavassolian1  Carlo Menon1  | |
[1] Menrva Research Group Schools of Mechatronic Systems & Engineering Science Simon Fraser University Metro Vancouver BC V5A1S6 Canada; | |
关键词: inductive sensors; kinematic tracking; smart sensors; soft sensors; wearable devices; | |
DOI : 10.1002/aisy.201900165 | |
来源: DOAJ |
【 摘 要 】
Wearable multiaxes motion tracking with inductive sensors and machine learning is presented. The production, characterization, and use of a modular and size‐adjustable inductive sensor for kinematic motion tracking are introduced. The sensor is highly stable and able to track high‐frequency (>15 Hz) and high strain rates (>450% s−1). Four sensors are used to fabricate a pair of motion capture shorts. A random forest machine learning algorithm is used to predict the sagittal, transverse, and frontal hip joint angle, using the raw signals from sport shorts during running with a cohort of 12 participants against a gold standard optical motion capture system to an accuracy as high as R2 = 0.98 and root mean squared error of 2° in all three planes. Herein, an alternative strain sensor is provided to those typically used (piezoresistive/capacitive) for soft wearable motion capture devices with distinct advantages that can find applications in smart wearable devices, robotics, or direct integration into textiles.
【 授权许可】
Unknown